Performance Evaluation of Directionally Performance Evaluation of Directionally Separation of Noisy Observations

Abstract

Separation performance of directionally constrained filterbank ICA is evaluated in presence of noise with different spectral properties. Stationarity ofmixing channels is exploited to introduce directional constraint on the adaptive subband separation networks of filterbankbased blind source separation approach. Directional constraints on demixing network improves separation of source signals from noisy convolved mixtures, when significant spectral overlap exists between the noise and the convolved mixtures.Observations corrupted with low frequency noises exhibit slight improvement in the separation performance as there is less spectral overlap. Initialization and constraining of subband demixing network in accordance to the spatial location of source signals results in faster convergence and effective permutation correction, irrespective, of the nature of additive noise.